39 citations · 112 across the 29 of their papers we have counts for
30 papers
JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space
Xinnan Zhu, Ruijie Xu, Jiayu Ying +4
Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelines, resulting in high test-time…
S2D: Sparse to Dense Lifting for 3D Reconstruction with Minimal Inputs
Yuzhou Ji, Qijian Tian, He Zhu +5
Explicit 3D representations have already become an essential medium for 3D simulation and understanding. However, the most commonly used point cloud and 3D Gaussian Splatting (3DGS…
Explore with Long-term Memory: A Benchmark and Multimodal LLM-based Reinforcement Learning Framework for Embodied Exploration
Sen Wang, Bangwei Liu, Zhenkun Gao +4
An ideal embodied agent should possess lifelong learning capabilities to handle long-horizon and complex tasks, enabling continuous operation in general environments. This not only…
FLEG: Feed-Forward Language Embedded Gaussian Splatting from Any Views via Compact Semantic Representation
Qijian Tian, Xin Tan, Jiayu Ying +3
We present FLEG, a feed-forward network that reconstructs language-embedded 3D Gaussians from arbitrary views. Previous feed-forward language-embedded Gaussian reconstruction metho…
PFDepth: Heterogeneous Pinhole-Fisheye Joint Depth Estimation via Distortion-aware Gaussian-Splatted Volumetric Fusion
Zhiwei Zhang, Ruikai Xu, Weijian Zhang +5
In this paper, we present the first pinhole-fisheye framework for heterogeneous multi-view depth estimation, PFDepth. Our key insight is to exploit the complementary characteristic…
From Enhancement to Understanding: Build a Generalized Bridge for Low-light Vision via Semantically Consistent Unsupervised Fine-tuning
Sen Wang, Shao Zeng, Tianjun Gu +8
Low-level enhancement and high-level visual understanding in low-light vision have traditionally been treated separately. Low-light enhancement improves image quality for downstrea…
MOL: Joint Estimation of Micro-Expression, Optical Flow, and Landmark via Transformer-Graph-Style Convolution
Zhiwen Shao, Yifan Cheng, Feiran Li +4
Facial micro-expression recognition (MER) is a challenging problem, due to transient and subtle micro-expression (ME) actions. Most existing methods depend on hand-crafted features…
UniForward: Unified 3D Scene and Semantic Field Reconstruction via Feed-Forward Gaussian Splatting from Only Sparse-View Images
Qijian Tian, Xin Tan, Jingyu Gong +2
We propose a feed-forward Gaussian Splatting model that unifies 3D scene and semantic field reconstruction. Combining 3D scenes with semantic fields facilitates the perception and…
SHTOcc: Effective 3D Occupancy Prediction with Sparse Head and Tail Voxels
Qiucheng Yu, Yuan Xie, Xin Tan
3D occupancy prediction has attracted much attention in the field of autonomous driving due to its powerful geometric perception and object recognition capabilities. However, exist…
DORAEMON: Decentralized Ontology-aware Reliable Agent with Enhanced Memory Oriented Navigation
Tianjun Gu, Linfeng Li, Xuhong Wang +6
Adaptive navigation in unfamiliar environments is crucial for household service robots but remains challenging due to the need for both low-level path planning and high-level scene…
Hydra-MDP++: Advancing End-to-End Driving via Expert-Guided Hydra-Distillation
Kailin Li, Zhenxin Li, Shiyi Lan +6
Hydra-MDP++ introduces a novel teacher-student knowledge distillation framework with a multi-head decoder that learns from human demonstrations and rule-based experts. Using a ligh…
One-for-More: Continual Diffusion Model for Anomaly Detection
Xiaofan Li, Xin Tan, Zhuo Chen +8
With the rise of generative models, there is a growing interest in unifying all tasks within a generative framework. Anomaly detection methods also fall into this scope and utilize…
Diffusion Implicit Policy for Unpaired Scene-aware Motion Synthesis
Jingyu Gong, Chong Zhang, Fengqi Liu +5
Scene-aware motion synthesis has been widely researched recently due to its numerous applications. Prevailing methods rely heavily on paired motion-scene data, while it is difficul…
DrivingForward: Feed-forward 3D Gaussian Splatting for Driving Scene Reconstruction from Flexible Surround-view Input
Qijian Tian, Xin Tan, Yuan Xie +1
We propose DrivingForward, a feed-forward Gaussian Splatting model that reconstructs driving scenes from flexible surround-view input. Driving scene images from vehicle-mounted cam…
PIG: Prompt Images Guidance for Night-Time Scene Parsing
Zhifeng Xie, Rui Qiu, Sen Wang +3
Night-time scene parsing aims to extract pixel-level semantic information in night images, aiding downstream tasks in understanding scene object distribution. Due to limited labele…
FastLGS: Speeding up Language Embedded Gaussians with Feature Grid Mapping
Yuzhou Ji, He Zhu, Junshu Tang +4
The semantically interactive radiance field has always been an appealing task for its potential to facilitate user-friendly and automated real-world 3D scene understanding applicat…
GEOcc: Geometrically Enhanced 3D Occupancy Network with Implicit-Explicit Depth Fusion and Contextual Self-Supervision
Xin Tan, Wenbin Wu, Zhiwei Zhang +5
3D occupancy perception holds a pivotal role in recent vision-centric autonomous driving systems by converting surround-view images into integrated geometric and semantic represent…
PromptAD: Learning Prompts with only Normal Samples for Few-Shot Anomaly Detection
Xiaofan Li, Zhizhong Zhang, Xin Tan +4
The vision-language model has brought great improvement to few-shot industrial anomaly detection, which usually needs to design of hundreds of prompts through prompt engineering. F…
DEMOS: Dynamic Environment Motion Synthesis in 3D Scenes via Local Spherical-BEV Perception
Jingyu Gong, Min Wang, Wentao Liu +4
Motion synthesis in real-world 3D scenes has recently attracted much attention. However, the static environment assumption made by most current methods usually cannot be satisfied…
COTR: Compact Occupancy TRansformer for Vision-based 3D Occupancy Prediction
Qihang Ma, Xin Tan, Yanyun Qu +3
The autonomous driving community has shown significant interest in 3D occupancy prediction, driven by its exceptional geometric perception and general object recognition capabiliti…
Generalized Category Discovery in Semantic Segmentation
Zhengyuan Peng, Qijian Tian, Jianqing Xu +5
This paper explores a novel setting called Generalized Category Discovery in Semantic Segmentation (GCDSS), aiming to segment unlabeled images given prior knowledge from a labeled…
Multi-modal In-Context Learning Makes an Ego-evolving Scene Text Recognizer
Zhen Zhao, Jingqun Tang, Chunhui Lin +6
Scene text recognition (STR) in the wild frequently encounters challenges when coping with domain variations, font diversity, shape deformations, etc. A straightforward solution is…
LiDAR-Camera Panoptic Segmentation via Geometry-Consistent and Semantic-Aware Alignment
Zhiwei Zhang, Zhizhong Zhang, Qian Yu +3
3D panoptic segmentation is a challenging perception task that requires both semantic segmentation and instance segmentation. In this task, we notice that images could provide rich…
AdaTriplet-RA: Domain Matching via Adaptive Triplet and Reinforced Attention for Unsupervised Domain Adaptation
Xinyao Shu, Shiyang Yan, Zhenyu Lu +2
Unsupervised domain adaption (UDA) is a transfer learning task where the data and annotations of the source domain are available but only have access to the unlabeled target data d…